--- license: apache-2.0 tags: - generated_from_trainer datasets: - news_commentary metrics: - bleu model-index: - name: opus-mt-ar-en-finetuned-ar-to-en results: - task: name: Sequence-to-sequence Language Modeling type: text2text-generation dataset: name: news_commentary type: news_commentary args: ar-en metrics: - name: Bleu type: bleu value: 32.5327 --- # opus-mt-ar-en-finetuned-ar-to-en This model is a fine-tuned version of [Helsinki-NLP/opus-mt-ar-en](https://huggingface.co/Helsinki-NLP/opus-mt-ar-en) on the news_commentary dataset. It achieves the following results on the evaluation set: - Loss: 10.6102 - Bleu: 32.5327 - Gen Len: 56.234 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 2e-09 - train_batch_size: 16 - eval_batch_size: 16 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 3 ### Training results | Training Loss | Epoch | Step | Validation Loss | Bleu | Gen Len | |:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:| | No log | 1.0 | 32 | 10.6112 | 32.5327 | 56.234 | | No log | 2.0 | 64 | 10.6103 | 32.5327 | 56.234 | | No log | 3.0 | 96 | 10.6102 | 32.5327 | 56.234 | ### Framework versions - Transformers 4.20.0 - Pytorch 1.11.0+cu113 - Datasets 2.3.2 - Tokenizers 0.12.1